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Remove references to the supplement in the main paper
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calculus.tex

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Limits are computed with the \verb|limit| function. The limit module
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implements the Gruntz algorithm~\cite{Gruntz1996limits} for computing symbolic
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limits (a description of the Gruntz algorithm may be found in the supplement).
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limits.
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For example, the following computes
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$\lim\limits_{x\to \infty} x\sin(\frac{1}{x})=1$. Note that SymPy denotes
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$\infty$ as \verb|oo|.

matrices.tex

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inference, they provide powerful reasoning over invertibility,
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semi-definiteness, orthogonality, etc., which are valuable in the construction
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of numerical linear algebra systems.
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More examples for \verb|Matrix| and \verb|BlockMatrix| may be found in the
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supplement.

paper.tex

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%%
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%% Quick overview of the main modules, what it can do and so on. It should probably provide examples how to use sympy.
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%%
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%% See also the supplement (below)
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\input{features}
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polys.tex

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$K[x_0][x_1]\dotso[x_n]$. Note that despite this, the coefficient domain $K$,
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can be a multivariate polynomial domain as well. The dense recursive
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representation in Python gets inefficient as the number of variables increases.
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Some examples for the \texttt{sympy.polys} module can be found in the
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supplement.

solvers.tex

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\texttt{solve}. There are certain features which are implemented in
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\texttt{solve} that are not yet implemented in \texttt{solveset}. Notably,
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these include nonlinear multivariate system and transcendental equations.
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More examples of \texttt{solveset} and \texttt{solve} can be found in the
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supplement.

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